Search results for: access network

Authors: Alexander Rodríguez-Hernández, Arnulfo Rojas-Perez, Liz Diaz-Vazquez

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The rise in consumerism over the past century has resulted in the creation of higher amounts of plasticizers, personal care products and other chemical substances, which enter and accumulate in water systems. Other sources of pollutants in Neotropical regions experience large inputs of nutrients with these pollutants resulting in eutrophication of water which consume large quantities of oxygen, resulting in high fish mortality. This dilemma has created a need for the development of targeted detection in complex matrices and remediation of emerging contaminants. We have synthesized carbon nanoparticles from macro algae (Ulva fasciata) by oxidizing the graphitic carbon network under extreme acidic conditions. The resulting material was characterized by STEM, yielding a spherical 12 nm average diameter nanoparticles, which can be fixed into a polysaccharide aerogel synthesized from the same macro algae. Spectrophotometer analyses show a pH dependent fluorescent behavior varying from 450-620 nm in aqueous media. Heavily oxidized edges provide for easy functionalization with enzymes for a more targeted analysis and remediation technique. Given the optical properties of the carbon base nanoparticles and the numerous possibilities of functionalization, we have developed a selective and robust targeted bio-detection and bioremediation technique for the treatment of emerging contaminants in complex matrices like estuarine embayment.

Keywords: aerogels, carbon nanoparticles, fluorescent, targeted analysis

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Authors: I Dewa Gede Arya Putra

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Principal Component Analysis (PCA) is a mathematical procedure that uses orthogonal transformation techniques to change a set of data with components that may be related become components that are not related to each other. This can have an impact on clustering wind speed characteristics in Indonesia. This study uses data daily wind speed observations of the Site Meteorological Station network for 30 years. Multicollinearity tests were also performed on all of these data before doing clustering with PCA. The results show that the four main components have a total diversity of above 80% which will be used for clusters. Division of clusters using Ward's method obtained 3 types of clusters. Cluster 1 covers the central part of Sumatra Island, northern Kalimantan, northern Sulawesi, and northern Maluku with the climatological pattern of wind speed that does not have an annual cycle and a weak speed throughout the year with a low-speed ranging from 0 to 1,5 m/s². Cluster 2 covers the northern part of Sumatra Island, South Sulawesi, Bali, northern Papua with the climatological pattern conditions of wind speed that have annual cycle variations with low speeds ranging from 1 to 3 m/s². Cluster 3 covers the eastern part of Java Island, the Southeast Nusa Islands, and the southern Maluku Islands with the climatological pattern of wind speed conditions that have annual cycle variations with high speeds ranging from 1 to 4.5 m/s².

Keywords: PCA, cluster, Ward's method, wind speed

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Authors: Jonas Colin

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Standing at the vanguard of AI development, Alpha represents an unprecedented synthesis of logical rigor and human abstraction, meticulously crafted to mirror the user's unique persona and personality, a feat previously unattainable in AI development. Alpha, an avant-garde artefact in the realm of artificial intelligence, epitomizes a paradigmatic shift in personalized digital interaction, amalgamating user-specific dialogic patterns with the sophisticated algorithmic prowess of OpenAI's GPT-3.5 to engender a platform for enhanced metacognitive engagement and individualized user experience. Underpinned by a sophisticated algorithmic framework, Alpha integrates vast datasets through a complex interplay of neural network models and symbolic AI, facilitating a dynamic, adaptive learning process. This integration enables the system to construct a detailed user profile, encompassing linguistic preferences, emotional tendencies, and cognitive styles, tailoring interactions to align with individual characteristics and conversational contexts. Furthermore, Alpha incorporates advanced metacognitive elements, enabling real-time reflection and adaptation in communication strategies. This self-reflective capability ensures continuous refinement of its interaction model, positioning Alpha not just as a technological marvel but as a harbinger of a new era in human-computer interaction, where machines engage with us on a deeply personal and cognitive level, transforming our interaction with the digital world.

Keywords: chatbot, GPT 3.5, metacognition, symbiose

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Authors: Amin Aghatabar Roodbary, Mohammad Hassan Bastani

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One of the defects of stepped frequency radar systems is their sensitivity to target motion. In such systems, target motion causes range cell shift, false peaks, Signal to Noise Ratio (SNR) reduction and range profile spreading because of power spectrum interference of each range cell in adjacent range cells which induces distortion in High Resolution Range Profile (HRRP) and disrupt target recognition process. Thus Target Motion Parameters (TMPs) effects compensation should be employed. In this paper, such a method for estimating TMPs (velocity and acceleration) and consequently eliminating or suppressing the unwanted effects on HRRP based on entropy minimization has been proposed. This method is carried out in two major steps: in the first step, a discrete search method has been utilized over the whole acceleration-velocity lattice network, in a specific interval seeking to find a less-accurate minimum point of the entropy function. Then in the second step, a 1-D search over velocity is done in locus of the minimum for several constant acceleration lines, in order to enhance the accuracy of the minimum point found in the first step. The provided simulation results demonstrate the effectiveness of the proposed method.

Keywords: automatic target recognition (ATR), high resolution range profile (HRRP), motion compensation, stepped frequency waveform technique (SFW), target motion parameters (TMPs)

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Authors: V. Nagammai

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Very-large-scale integration (VLSI) is the process of creating an integrated circuit (IC) by combining thousands of transistors into a single chip. Development of technology increases the complexity in IC manufacturing which may vary the power consumption, increase the size and latency period. Topology defines a number of connections between network. In this project, NoC topology is generated using atlas tool which will increase performance in turn determination of constraints are effective. The routing is performed by XY routing algorithm and wormhole flow control. In NoC topology generation, the value of power, area and latency are predetermined. In previous work, placement, routing and shortest path evaluation is performed using an algorithm called floor planning with cluster reconstruction and path allocation algorithm (FCRPA) with the account of 4 3x3 switch, 6 4x4 switch, and 2 5x5 switches. The usage of the 4x4 and 5x5 switch will increase the power consumption and area of the block. In order to avoid the problem, this paper has used one 8x8 switch and 4 3x3 switches. This paper uses IPRCA which of 3 steps they are placement, clustering, and shortest path evaluation. The placement is performed using min – cut placement and clustering are performed using an algorithm called cluster generation. The shortest path is evaluated using an algorithm called Dijkstra's algorithm. The power consumption of each block is determined. The experimental result shows that the area, power, and wire length improved simultaneously.

Keywords: application specific noc, b* tree representation, floor planning, t tree representation

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Authors: Syed Ahsan, Saleh Alshomrani, Ishtiaq Rasool, Ali Hassan

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In this oral presentation, we will provide an overview of the technical and semantic architecture of a desert border security and critical infrastructure protection security system. Modern border security systems are designed to reduce the dependability and intrusion of human operators. To achieve this, different types of sensors are use along with video surveillance technologies. Application of these technologies in a harsh desert environment of Saudi Arabia poses unique challenges. Environmental and geographical factors including high temperatures, desert storms, temperature variations and remoteness adversely affect the reliability of surveillance systems. To successfully implement a reliable, effective system in a harsh desert environment, the following must be achieved: i) Selection of technology including sensors, video cameras, and communication infrastructure that suit desert environments. ii) Reduced power consumption and efficient usage of equipment to increase the battery life of the equipment. iii) A reliable and robust communication network with efficient usage of bandwidth. Also, to reduce the expert bottleneck, an ontology-based intelligent information systems needs to be developed. Domain knowledge unique and peculiar to Saudi Arabia needs to be formalized to develop an expert system that can detect abnormal activities and any intrusion.

Keywords: border security, sensors, abnormal activity detection, ontologies

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Authors: Sohaib Raza, Parvez Mantry

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Frailty is a multi-system impairment associated with stressors such as age, disease, and invasive surgical procedures. This multi-system impairment can lead to increased post-transplant mortality and functional decline. Additionally, the prevalence and/or severity of frailty increases when patient pre-habilitation is unsatisfactory or lacking. We conducted a retrospective study to examine whether the COVID-19 Pandemic, and subsequent lack of patient access to pre-habilitation and physical therapy resources, led to an increase in the prevalence and severity of frailty, sarcopenia, and other comorbidities including diabetes, hypertension, and COPD. Secondarily, we examined the correlation between patient survival rate and liver frailty index as well as muscle wasting/sarcopenia. Data were analyzed in order to correlate variables associated with these parameters. Three hundred sixty-nine liver transplant candidates at Methodist Dallas Medical Center were administered pre-transplant frailty assessments, which consisted of chair stands, grip strength, and position balance time. A frailty score less than 3.2 indicated a robust condition, a score from 3.3 to 4.4 indicated a pre-frail condition, and a score greater than 4.5 indicated a frail condition. Greater than 50 percent of patients were found to have muscle wasting in the COVID-19 period (March 13, 2020 to February 28, 2022), an increase of 16.5 percent from the pre-COVID period (April 1st, 2018 to March 12, 2020). Additionally, sarcopenia was associated with a two-fold increase in patient mortality rate. Furthermore, high liver frailty index scores were associated with increased patient mortality. However, there was no significant difference in liver frailty index or number of comorbidities between patients in the two cohorts. Conclusion: The COVID-19 Pandemic exacerbated sarcopenia-related muscle wasting in liver transplant candidates, and patient survival rate was directly correlated with liver frailty index score and the presence of sarcopenia.

Keywords: frailty, sarcopenia, covid-19, patient mortality, pre-habilitation, liver transplant candidates

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Authors: Elham Rajabian

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The ascent of cybersecurity incidents is a rising threat to most organisations in general, while the impact of the incidents is unique to each of the organizations. It is a need for behavioural sciences to concentrate on employees’ behaviour in order to prepare key security mitigation opinions versus cybersecurity incidents. There are noticeable differences among users of a computer system in terms of complying with security behaviours. We can discuss the people's differences under several subjects such as delaying tactics on something that must be done, the tendency to act without thinking, future thinking about unexpected implications of present-day issues, and risk-taking behaviours in security policies compliance. In this article, we introduce high-profile cyber-attacks and their impacts on weakening cyber resiliency in organizations. We also give attention to human errors that influence network security. Human errors are discussed as a part of psychological matters to enhance compliance with the security policies. The organizational challenges are studied in order to shape a sustainable cyber risks management approach in the related work section. Insiders’ behaviours are viewed as a cyber security gap to draw proper cyber resiliency in section 3. We carry out the best cybersecurity practices by discussing four CIS challenges in section 4. In this regard, we provide a guideline and metrics to measure cyber resilience in organizations in section 5. In the end, we give some recommendations in order to build a cybersecurity culture based on individual behaviours.

Keywords: cyber resilience, human factors, cybersecurity behavior, attitude, usability, security culture

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Authors: Dung V. H. Pham, Kathryn Cullen

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Introduction: 40% of adolescents with major depression (MDD) are unresponsive to 1st line antidepressant treatment. The neural mechanism underlying treatment-responsive and treatment-resistant depression in adolescent are unclear. Amygdala is important for emotion processing and has been implicated in mood disorders. Past research has shown abnormal amygdala connectivity in adolescents with MDD. This research study changes in amygdala resting-state functional connectivity to find neural correlates of successful antidepressant treatment. Methods: Thirteen adolescents aged 12-19 underwent rfMRI before and after 8-week antidepressant treatment and completed BDI-II at each scan. A whole-brain approach, using anatomically defined amygdala ROIs (1) identified brain regions that are highly synchronous with the amygdala, (2) correlated neural changes with changes in overall depression and specific symptom clusters within depression. Results: Some neural correlates were common across domains: (1) decreased amygdala RSFC with the default mode network (posterior cingulate, precuneus) is associated with improvement in overall depression and many symptom clusters, (2) increased amygdala RSFC with fusiform gyrus is associated with symptom improvement across many symptom clusters. We also found unique neural changes associated with symptom improvement in each symptom cluster. Conclusion: This is the first preliminary study that looks at neural correlates of antidepressant treatment response to overall depression as well as different clusters of symptoms of depression. The finding suggests both overlapping and distinct neural mechanisms underlying improvement in each symptom clusters within depression. Some brain regions found are also implicated in MDD among adults in previous literature.

Keywords: depression, adolescents, fMRI, antidepressants

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Authors: Małgorzata Osowiecka

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Negative emotions are rather seen as creativity inhibitor. On the other hand, it is worth noting that negative emotions may be good for our functioning. Negative emotions enhance cognitive resources and improve evaluative processes. Moreover maintaining a negative emotional state allow for cognitive reinterpretation of the emotional stimuli, what is good for our creativity, especially cognitive flexibility. Writing a diary or writing about difficult emotional experiences in general can be the way to not only improve psychical health, but also – enhance creative behaviors. Thanks to translating difficult emotions to the verbal level and giving them ‘a name’ or ‘a label’, we can get easier access to both emotional content of an experience and to the semantic content, without the need of speaking out loud. Expressive writing improves academic results and the efficiency of working memory. The classical method of writing about emotions consists in a long-term process of describing negative experiences. Present research demonstrate the efficiency of this process over a shorter period of time - one writing session, on school children sample. Participants performed writing task. Writing task had two different topics: emotions connected with their negative emotions (expressive writing) and content not connected with negative emotional state (writing about one’s typical day). Creativity was measured by Guilford’s Alternative Uses Task. Results have shown that writing about negative emotions results in the higher level of divergent thinking in all three parameters: fluency, flexibility and originality. After the writing task mood of expressive writing participants remained negative more than the mood of the controls. Taking an expressive action after a difficult emotional experience can support functioning, which can be observed in enhancement of divergent thinking. Writing about emotions connected with negative experience makes one more creative, than writing about something unrelated with difficult emotional moments. Research has shown that young people should not demonize negative emotions. Sometimes, properly applied, negative emotions can be the basis of creation. Preparation was supported by a The Young Scientist University grant titled ‘Dynamics of emotions in the creative process’ from The Polish Ministry of Science and Higher Education.

Keywords: creativity, divergent thinking, emotions, expressive writing

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Authors: Lene Granzau Juel-Jacobsen

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The problem of beautification is an obvious concern of photography, claiming reference to reality, but it also lies at the very heart of social theory. As we become accustomed to sophisticated visualizations of statistical data in pace with the development of software programs, we should not only be inclined to ask new types of research questions, but we also need to confront social theories based on such visualization techniques with new types of questions. Correspondence Analysis, GIS analysis, Social Network Analysis, and Perceptual Maps are current examples of visualization techniques popular within the social sciences and neighboring disciplines. This article discusses correspondence analysis, arguing that the graphic plot of correspondence analysis is to be interpreted much similarly to a photograph. It refers no more evidently or univocally to reality than a photograph, representing social life no more truthfully than a photograph documents. Pierre Bourdieu’s theoretical corpus, especially his theory of fields, relies heavily on correspondence analysis. While much attention has been directed towards critiquing the somewhat vague conceptualization of habitus, limited focus has been placed on the equally problematic concepts of social space and field. Based on a re-reading of the Distinction, the article argues that the concepts rely on ‘a small graphic lie’ very similar to a photograph. Like any other piece of art, as Bourdieu himself recognized, the graphic display is a politically and morally loaded representation technique. However, the correspondence analysis does not necessarily serve the purpose he intended. In fact, it tends towards the pitfalls he strove to overcome.

Keywords: datavisualization, correspondance analysis, bourdieu, Field, visual representation

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Authors: Yahia A. M. AlKhoudary

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This Study presents the outcome of an investigation to evaluate the importance of autonomous learning as a means of motivation. However, very little research done in this field. Thus, the aims of this study are to ascertain the needs of the learners and to investigate their attitudes and motivation towards the mode of learning. Various suggestions made on how to improve learners’ participation in the learning process. A survey conducted on a sample group of 60 Omani College students. Self-report questionnaires and retrospective interviews conducted to find out their material-type preferences in a self-access learning context. Achieving autonomous learning system, which learners is one of the Ministry of Education goals in the Sultanate of Oman. As a result, this study presents the outcome of an investigation to evaluate the students’ performance in English as a Foreign Language (EFL). It focuses on the effect of autonomous learning that encourages students to learn English, a research conducted at Buraimi city, the Sultanate of Oman. The procedure of this investigation based on four dimensions: (1) sixty students are selected and divided into two groups, (2) pre and posttest projects are given to them, and (3) questionnaires are administered to both students who are involved in the experiment and 50 teachers (25 males and 25 females) to collect accurate data, (4) an interview with students and teachers to find out their attitude towards autonomous learning. Analysis of participants’ responses indicated that autonomous learning motivates students to learn English independently and increase the intrinsic rather than extrinsic motivation to improve their English language as a long-life active learning. The findings of this study show that autonomous learning approach is the best remedy to empower the students’ skills and overcome all relevant difficulties. They also show that secondary school teachers can fully rely on this learning approach that encourages language learners to monitor their progress, increase both learners and teachers’ motivation and ameliorate students’ behavior in the classroom. This approach is also an ongoing process, which takes time, patience and support to be lifelong learning.

Keywords: Omani, autonomous learning system, English as a Foreign Language (EFL), learning approach

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Authors: Vivian Polak, Lena Verdeli, Wendy Lou, Caroline Lovett

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Postnatal depression (PND) is a common complication of childbirth that increases the risk of future depressive episodes in women, postpartum depression in partners, as well as social, emotional, behavioural, language, and cognitive problems in offspring. Although psychotherapy, and in particular Group Interpersonal Psychotherapy (IPT-G), has been proven effective in treating PND, it remains largely inaccessible. However, research has indicated that online synchronous group therapy can be equally as effective as in-person therapy and is a more affordable and accessible modality of treatment. This study aimed to ascertain whether delivering IPT-G virtually when compared to treatment as usual, could more effectively reduce depressive and anxiety symptoms, enhance mother-infant attachment, improve the couple relationship, augment social support, improve overall functioning, and enhance the quality of life for women in rural and northern Ontario who are suffering from PND. By bridging the gap in access to mental health services during the postpartum period, this study seeks to improve the well-being of mothers and their families in rural and northern Ontario, Canada. A randomized controlled trial was conducted to determine whether virtual IPT-G plus treatment as usual would be more effective than treatment as usual alone in treating women with PND in Ontario, Canada. Preliminary results indicate that women who received virtual IPT-G had a clinically and statistically significant decrease in overall depressive symptoms compared to their counterparts who received only the treatment as usual. As such, providing online synchronous IPT-G in the perinatal period not only has the potential to improve women's outcomes in the present but also to decrease future health costs, reduce the burden on the educational and justice systems, and decrease the number of disability life years lost to postnatal depression.

Keywords: family wellbeing, group psychotherapy, interpersonal psychotherapy, postnatal depression, virtual psychotherapy

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Authors: Chandra Mukherjee

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The prevalent knowledge of the biological systems is based on the standard scientific perception of natural equilibrium, determination and predictability. Recently, a rethinking of concepts was presented and a new scientific perspective emerged that involves complexity theory with deterministic chaos theory, nonlinear dynamics and theory of fractals. The unpredictability of the chaotic processes probably would change our understanding of diseases and their management. The mathematical definition of chaos is defined by deterministic behavior with irregular patterns that obey mathematical equations which are critically dependent on initial conditions. The chaos theory is the branch of sciences with an interest in nonlinear dynamics, fractals, bifurcations, periodic oscillations and complexity. Recently, the biomedical interest for this scientific field made these mathematical concepts available to medical researchers and practitioners. Any biological network system is considered to have a nominal state, which is recognized as a homeostatic state. In reality, the different physiological systems are not under normal conditions in a stable state of homeostatic balance, but they are in a dynamically stable state with a chaotic behavior and complexity. Biological systems like heart rhythm and brain electrical activity are dynamical systems that can be classified as chaotic systems with sensitive dependence on initial conditions. In biological systems, the state of a disease is characterized by a loss of the complexity and chaotic behavior, and by the presence of pathological periodicity and regulatory behavior. The failure or the collapse of nonlinear dynamics is an indication of disease rather than a characteristic of health.

Keywords: HRV, HRVI, LF, HF, DII

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Authors: Riaan Kleyn

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Mass wine production companies across the globe are provided with grapes from winegrowers that predominantly utilize mechanical harvesting machines to harvest wine grapes. Mechanical harvesting accelerates the rate at which grapes are harvested, allowing grapes to be delivered faster to meet the demands of wine cellars. The disadvantage of the mechanical harvesting method is the inclusion of material-other-than-grapes (MOG) in the harvested wine grape loads arriving at the cellar which degrades the quality of wine that can be produced. Currently, wine cellars do not have a method to determine the amount of MOG present within wine grape loads. This paper seeks to find an optimal computer vision method capable of detecting the amount of MOG within a wine grape load. A MOG detection method will encourage winegrowers to deliver MOG-free wine grape loads to avoid penalties which will indirectly enhance the quality of the wine to be produced. Traditional image segmentation methods were compared to deep learning segmentation methods based on images of wine grape loads that were captured at a wine cellar. The Mask R-CNN model with a ResNet-50 convolutional neural network backbone emerged as the optimal method for this study to determine the amount of MOG in an image of a wine grape load. Furthermore, a statistical analysis was conducted to determine how the MOG on the surface of a grape load relates to the mass of MOG within the corresponding grape load.

Keywords: computer vision, wine grapes, machine learning, machine harvested grapes

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Authors: Zhipeng Chen, Peng Zhang, Qingyun Liu, Li Guo

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With the Internet becoming the dominant channel for business and life, many IPs are increasingly masked using web proxies for illegal purposes such as propagating malware, impersonate phishing pages to steal sensitive data or redirect victims to other malicious targets. Moreover, as Internet traffic continues to grow in size and complexity, it has become an increasingly challenging task to detect the proxy service due to their dynamic update and high anonymity. In this paper, we present an approach based on behavioral graph analysis to study the behavior similarity of web proxy users. Specifically, we use bipartite graphs to model host communications from network traffic and build one-mode projections of bipartite graphs for discovering social-behavior similarity of web proxy users. Based on the similarity matrices of end-users from the derived one-mode projection graphs, we apply a simple yet effective spectral clustering algorithm to discover the inherent web proxy users behavior clusters. The web proxy URL may vary from time to time. Still, the inherent interest would not. So, based on the intuition, by dint of our private tools implemented by WebDriver, we examine whether the top URLs visited by the web proxy users are web proxies. Our experiment results based on real datasets show that the behavior clusters not only reduce the number of URLs analysis but also provide an effective way to detect the web proxies, especially for the unknown web proxies.

Keywords: bipartite graph, one-mode projection, clustering, web proxy detection

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Authors: Bougema Theodore Ntenkeh, Chi-bikom Barbara Kyien

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The reduction of poverty and hunger sits at the heart of the United Nations 2030 Agenda for Sustainable Development, and are the first two of the Sustainable Development Goals. The World Food Day celebrated on the 16th of October every year, highlights the need for people to have physical and economic access at all times to enough nutritious and safe food to live a healthy and active life; while the world poverty day celebrated on the 17th of October is an opportunity to acknowledge the struggle of people living in poverty, a chance for them to make their concerns heard, and for the community to recognize and support poor people in their fight against poverty. The association between household food security and poverty reduction is not only sparse in Cameroon but mostly qualitative. The paper therefore investigates the effect of household food security on poverty reduction in Cameroon quantitatively using data from the Cameroon Household Consumption Survey collected by the Government Statistics Office. The methodology employed five indicators of household food security using the Multiple Correspondence Analysis and poverty is captured as a dummy variable. Using a control function technique, with pre and post estimation test for robustness, the study postulates that household food security has a positive and significant effect on poverty reduction in Cameroon. A unit increase in the food security score reduces the probability of the household being poor by 31.8%, and this effect is statistically significant at 1%. The result further illustrates that the age of the household head and household size increases household poverty while households residing in urban areas are significantly less poor. The paper therefore recommends that households should diversify their food intake to enhance an effective supply of labour in the job market as a strategy to reduce household poverty. Furthermore, family planning methods should be encouraged as a strategy to reduce birth rate for an equitable distribution of household resources including food while the government of Cameroon should also develop the rural areas given that trend in urbanization are associated with the concentration of productive economic activities, leading to increase household income, increased household food security and poverty reduction.

Keywords: food security, poverty reduction, SDGs, Cameroon

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Authors: Alexander G. Yushchenko

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From a multi-science point of view, we analyze threats to security resulting from globalization of international information space and information and communication aggression of Russia. A definition of Ruschism is formulated as an ideology supporting aggressive actions of modern Russia against the Euro-Atlantic community. Stages of the hybrid war Russia is leading against Ukraine are described, including the elements of subversive activity of the special services, the activation of the military phase and the gradual shift of the focus of confrontation to the realm of information and communication technologies. We reveal an emergence of a threat for democratic states resulting from the destabilizing impact of a target state’s mass media and social networks being exploited by Russian secret services under freedom-of-speech disguise. Thus, we underline the vulnerability of cyber- and information security of the network society in regard of hybrid war. We propose to define the latter a synergetic war. Our analysis is supported with a long-term qualitative monitoring of representation of top state officials on popular TV channels and Facebook. From the memetics point of view, we have detected a destructive psycho-information technology used by the Kremlin, a kind of information catastrophe, the essence of which is explained in detail. In the conclusion, a comprehensive plan for information protection of the public consciousness and mentality of Euro-Atlantic citizens from the aggression of the enemy is proposed.

Keywords: cyber and information security, hybrid war, psycho-information technology, synergetic war, Ruschism

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Authors: Anita Chhatwal

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Purpose: The purpose of this paper is to evaluate and investigate the scope of usage of Academic Social Networking Websites (ASNs) by the Science faculty members across universities of North India, viz. Panjab University, Punjabi University and University of Delhi, Delhi. Design/Methodology/Approach: The present study is based upon the primary data collected from 81 science faculty participants from three universities of North India. Questionnaire method was used as an instrument for survey. The study is descriptive and research-based to investigate the popular ASNs amongst the participants from three sample universities and the purpose for which they use them along with the problems they encounter while using ASNs. Findings: The findings of the study revealed that majority of the participants were using ASNs for their academic needs. It was observed that majority of the participants (78%) used ASNs to access scientific papers, while 73.8% of the participants used them to share their research publications. ResearchGate (60.5%) and Google Scholar (59.7%) were the top two most preferred and widely used ASNs by the participants. The critical analysis of the data shows that laptops (86.3%) emerged as major tools for accessing ASNs. Shortage of computers was found to be the chief obstacle in accessing ASNs by the participants. Results of the study demonstrate that 56.3% of participants suggested conduct of seminars and training as the most effective method to increase the awareness of ASNs. Research Limitations/Implications: The study in hand absorbed the 81 faculty (Assistant Professors) members from 15 Science teaching departments across three sample universities of North India. The findings of this study will help the Government of India to regulate and simultaneously make effort to develop and enhance ASNs usage among faculty, researchers, and students. The present study will add to the existing library and information science literature and will be advantageous for all the information professionals as well. Originality/Value: This study is original survey based on primary data investigate the usage of ASNs by the academia. This study will be useful for research scholars, academicians and students all over the world.

Keywords: academic social networks, awareness and usage, North India, scholarly communication, web 2.0

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Authors: Ansari Mohammad Reza, Hiroko Ono, Fakhrullah Sarwari

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Our world is fast heading toward being a predominantly urban planet. This can be a double-edged sword reality where it is as much frightening as it seems interesting. Moreover, a look to the current predictions and taking into the consideration the fact that about 90 percent of the coming urbanization is going to be absorbed by the towns and the cities of the developing countries of Asia and Africa, directly provide us the clues to assume a much more tragic ending to this story than to the happy one. Likewise, in a situation wherein most of these countries are still severely struggling to find the proper answer to their very first initial questions of urbanization—e.g. how to provide the essential structure for their cities, define the regulation, or even design the proper pattern on how the cities should be expanded—thus it is not weird to claim that most of the coming urbanization of the world is going to happen informally. This reality could not only bring the feature, landscape or the picture of the cities of the future under the doubt but at the same time provide the ground for the rise of a bunch of other essential questions of how the facilities would be distributed in these cities, or how fair will this pattern of distribution be. Kabul the capital of Afghanistan, as a city located in the developing world that its process of urbanization has been starting since 2001 and currently hold the position to be the fifth fastest growing city in the world, contained to a considerable slum ratio of 0.7—that means about 70 percent of its population is living in the informal areas—subsequently could be a very good case study to put this questions into the research and find out how the informal development of a city can lead to the unfair and unbalanced distribution of its facilities. Likewise, in this study we tried our best to first propose the ideal model for the fair distribution of the facilities in the Kabul city—where all the citizens have the same equal chance of access to the facilities—and then evaluate the situation of the city based on how fair the facilities are currently distributed therein. We subsequently did it by the comparative analysis between the existing facility rate in the formal and informal areas of the city to the one that was proposed as the fair ideal model.

Keywords: Afghanistan, facility distribution, formal settlements, informal settlements, Kabul

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Authors: Messaoud Eljamai, Sami Hidouri

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Massive multiple-input multiple-output (MIMO) is an emerging technology for new cellular networks such as 5G systems. Its principle is to use many antennas per cell in order to maximize the network's spectral efficiency. Inter-cellular interference remains a fundamental problem. The use of massive MIMO will not derogate from the rule. It improves performances only when the number of antennas is significantly greater than the number of users. This, considerably, limits the networks spectral efficiency. In this paper, a coordinated detector for an uplink massive MIMO system is proposed in order to mitigate the inter-cellular interference. The proposed scheme combines the coordinated multipoint technique with an interference-cancelling algorithm. It requires the serving cell to send their received symbols, after processing, decision and error detection, to the interfered cells via a backhaul link. Each interfered cell is capable of eliminating intercellular interferences by generating and subtracting the user’s contribution from the received signal. The resulting signal is more reliable than the original received signal. This allows the uplink massive MIMO system to improve their performances dramatically. Simulation results show that the proposed detector improves system spectral efficiency compared to classical linear detectors.

Keywords: massive MIMO, COMP, interference canceling algorithm, spectral efficiency

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Authors: Yelbek B. Utepov, Assel S. Tulebekova, Alizhan B. Kazkeyev

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Maturity sensors are used to determine concrete strength by the non-destructive method. The method of placement of the maturity sensors determines their number required for a certain frame of a monolithic building. Previous studies weakly describe this aspect, giving only logical assumptions. This paper proposes a cheap prototype of an embedded wireless sensor for monitoring concrete structures, as well as an alternative strategy for placing sensors based on the transitional boundaries of the temperature distribution of concrete curing, which were determined by building a heat map of the temperature distribution, where unknown values are calculated by the method of inverse distance weighing. The developed prototype can simultaneously measure temperature and relative humidity over a smartphone-controlled time interval. It implements a maturity method to assess the in-situ strength of concrete, which is considered an alternative to the traditional shock impulse and compression testing method used in Kazakhstan. The prototype was tested in laboratory and field conditions. The tests were aimed at studying the effect of internal and external temperature and relative humidity on concrete's strength gain. Based on an experimentally poured concrete slab with randomly integrated maturity sensors, it was determined that the transition boundaries form elliptical forms. Temperature distribution over the largest diameter of the ellipses was plotted, resulting in correct and inverted parabolas. As a result, the distance between the closest opposite crossing points of the parabolas is accepted as the maximum permissible step for setting the maturity sensors. The proposed placement strategy can be applied to sensors that measure various continuous phenomena such as relative humidity. Prototype testing has also revealed Bluetooth inconvenience due to weak signal and inability to access multiple prototypes simultaneously. For this reason, further prototype upgrades are planned in future work.

Keywords: heat map, placement strategy, temperature and relative humidity, wireless embedded sensor

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Authors: Wesley Too, Christine Chesiror

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Hypertension is a public health challenge that globally, with the World Health Organization estimating that by 2025, more than 1.5 billion people would have been diagnosed with it. Kenya’s prevalence of hypertension is estimated at 24.6 percent; however, 55% of the affected have uncontrolled blood pressure, which is worst in some parts of the country with different lifestyle: nomads and migratory communities. Kenyan pastoralists comprise 20% of the nation's population and are constantly on the move for search of water, pasture for their herd, and desertification have driven nomadic populations to the brink, given their unique and dynamic challenges. Nomads face myriad of challenges and barriers towards the management of their health care problems. Nomadic area is predominantly rural, with a low population density and a nomadic population. Health care access and quality are further hampered by poor telecommunications, infrastructure, and security. In Kenya, nomadic communities experience the worst health outcomes, disproportionate health disparities, and inequalities due to unresponsive, culturally sensitive health care system to nomad’s lifestyle and their health care needs. Marsabit covering a surface area of 66,923.1 km2, is the second largest county in Kenya, constituting about 2.3 million people of North-Eastern region, with only 2.3 percent and 1.9 percent of Kenya's total number of doctors and nurses in the country. In Kenya, there are scanty research on hypertension managementin this region and, at best, non-existent study on hypertension among nomads-migratory communities of Northern Kenya. Therefore, the purpose seeks to determine the prevalence of hypertension among nomads and document nomads' practices regarding early detections, management, and levels of control of hypertension in one of the Counties in Kenya with high- hypertensive case load per year. Methods: A cross-sectional study design was used to collect data from multiple sites and health facilities. A total of 260 participants were enrolled into the study. The study is currently ongoing. It is anticipated that by September, we will have initial findings & recommendations to share for conference

Keywords: pastoralists, hypertension, health, kenya

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Authors: Kishore Kumar R., Kaustav Sengupta, Shalini Sood Sehgal, Poornima Santhanam

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Fashion is a human expression that is constantly changing. One of the prime factors that consistently influences fashion is the change in colour preferences. The role of colour in our everyday lives is very significant. It subconsciously explains a lot about one’s mindset and mood. Analyzing the colours by extracting them from the outfit images is a critical study to examine the individual’s/consumer behaviour. Several research works have been carried out on extracting colours from images, but to the best of our knowledge, there were no studies that extract colours to specific apparel and identify colour patterns geographically. This paper proposes a framework for accurately extracting colours from T-shirt images and predicting dominant colours geographically. The proposed method consists of two stages: first, a U-Net deep learning model is adopted to segment the T-shirts from the images. Second, the colours are extracted only from the T-shirt segments. The proposed method employs the iMaterialist (Fashion) 2019 dataset for the semantic segmentation task. The proposed framework also includes a mechanism for gathering data and analyzing India’s general colour preferences. From this research, it was observed that black and grey are the dominant colour in different regions of India. The proposed method can be adapted to study fashion’s evolving colour preferences.

Keywords: colour analysis in t-shirts, convolutional neural network, encoder-decoder, k-means clustering, semantic segmentation, U-Net model

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Authors: Anna S. Tolkacheva, Sergey N. Shkerin, Kirill G. Zemlyanoi, Olga G. Reznitskikh, Pavel D. Khavlyuk

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Calcium oxovanadates with garnet related structure are multifunctional oxides in various fields like photoluminescence, microwave dielectrics, and magneto-dielectrics. For example, vanadate garnets are self-luminescent compounds. They attract attention as RE-free broadband excitation and emission phosphors and are candidate materials for UV-based white light-emitting diodes (WLEDs). Ca₅M₄(VO₄)₆ (M = Mg, Zn, Co, Ni, Mn) compounds are also considered promising for application in microwave devices as substrate materials. However, the relation between their structure, composition and physical/chemical properties remains unclear. Given the above-listed observations, goals of this study are to synthesise Ca₅M₄(VO₄)₆ (M = Mg, Zn, Ni) and to study their thermal and electrical properties. Solid solutions Ca₅Mg₄₋ₓMₓ(VO₄)₆ (0 ≤ x ≤ 4) where M is Zn and Ni have been synthesized by sol-gel method. The single-phase character of the final products was checked by powder X-ray diffraction on a Rigaku D/MAX-2200 X-ray diffractometer using Cu Kα radiation in the 2θ range from 15° to 70°. The dependence of thermal properties on chemical composition of solid solutions was studied using simultaneous thermal analyses (DSC and TG). Thermal analyses were conducted in a Netzch simultaneous analyser STA 449C Jupiter, in Ar atmosphere, in temperature range from 25 to 1100°C heat rate was 10 K·min⁻¹. Coefficients of thermal expansion (CTE) were obtained by dilatometry measurements in air up to 800°C using a Netzsch 402PC dilatometer; heat rate was 1 K·min⁻¹. Impedance spectra were obtained via the two-probe technique with an impedance meter Parstat 2273 in air up to 700°C with the variation of pH₂O from 0.04 to 3.35 kPa. Cation deficiency in Ca and Mg sublattice under the substitution of MgO with ZnO up to 1/6 was observed using Rietveld refinement of the crystal structure. Melting point was found to decrease with x changing from 0 to 4 in Ca₅Mg₄₋ₓMₓ(VO₄)₆ where M is Zn and Ni. It was observed that electrical conductivity does not depend on air humidity. The reported study was funded by the RFBR Grant No. 17–03–01280. Sample attestation was carried out in the Shared Access Centers at the IHTE UB RAS.

Keywords: garnet structure, electrical conductivity, thermal expansion, thermal properties

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Authors: Warnakulasuriya Arachichige Malisha Ann Rosary Fernando, Udalamatta Gamage Omila Chalanka Jinadasa, Bihini Pabasara Amandi Amarasinghe, Manul Thisuraka Mandalawatta, Uthpala Samarakoon, Manori Gamage

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The surge in sexually transmitted diseases (STDs) has become a critical public health crisis demanding urgent attention and action. Like many other nations, Sri Lanka is grappling with a significant increase in STDs due to a lack of education and awareness regarding their dangers. Presently, the available applications for tracking and managing STDs cover only a limited number of easily detectable infections, resulting in a significant gap in effectively controlling their spread. To address this gap and combat the rising STD rates, it is essential to leverage technology and data. Employing technology to enhance the tracking and management of STDs is vital to prevent their further propagation and to enable early intervention and treatment. This requires adopting a comprehensive approach that involves raising public awareness about the perils of STDs, improving access to affordable healthcare services for early detection and treatment, and utilizing advanced technology and data analysis. The proposed mobile application aims to cater to a broad range of users, including STD patients, recovered individuals, and those unaware of their STD status. By harnessing cutting-edge technologies like image detection, symptom-based identification, prevention methods, doctor and clinic recommendations, and virtual counselor chat, the application offers a holistic approach to STD management. In conclusion, the escalating STD rates in Sri Lanka and across the globe require immediate action. The integration of technology-driven solutions, along with comprehensive education and healthcare accessibility, is the key to curbing the spread of STDs and promoting better overall public health.

Keywords: STD, machine learning, NLP, artificial intelligence

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Authors: Kaleb Shiferaw, Berhanu Geberemedhin

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Ethiopian farmers have a long tradition of beekeeping and the country has huge potential for honey production. However traditional mode of production still dominates the sub sector which negatively affect the total production and productivity. A number of studies have been conducted to better understand the working honey production, however, none of them systematically investigate the extent of technical efficiency of the sub-sector. This paper uses Stochastic Frontier production model to quantifying the extent of technical efficiency and identify exogenous determinant of inefficiency. The result showed that consistent with other studies traditional practice dominate small scale honey production in Ethiopia. The finding also revealed that use of purchased inputs such as bee forage and other supplement is very limited among honey producers indicating that natural bee forage is the primary source of bee forage. The immediate consequence of all these is low production and productivity. The number of hives the household owns, whether the household used improved apiculture technologies, availability of natural forest which is the primary sources of nectar for bees and amount of land owned by the households were found to have a significant influence on the amount of honey produced by beekeeper. Our result further showed that the mean technical efficiency of honey producers is 0.79 implying that, on average honey producer produce 80 percent of the maximum output. The implication is that 20 percent of the potential output is lost due to technical inefficiency. Number of hives owned by a honey produces, distance to district town-a proxy to market access, household wealth, and whether the household head has a leadership role in the PA affect the technical efficiency of honey producers. The finding suggest that policies that aim to expand the use of improved hives is expected to increase the honey production at household level. The result also suggest that investment on rural infrastructure would be instrumental in improving technical efficiency of honey producer.

Keywords: small-scale honey producer, Ethiopia, technical efficiency in apiculture, stochastic frontier analysis

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Authors: A. Shoiynbek, K. Kozhakhmet, P. Menezes, D. Kuanyshbay, D. Bayazitov

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Speech emotion recognition has received increasing research interest all through current years. There was used emotional speech that was collected under controlled conditions in most research work. Actors imitating and artificially producing emotions in front of a microphone noted those records. There are four issues related to that approach, namely, (1) emotions are not natural, and it means that machines are learning to recognize fake emotions. (2) Emotions are very limited by quantity and poor in their variety of speaking. (3) There is language dependency on SER. (4) Consequently, each time when researchers want to start work with SER, they need to find a good emotional database on their language. In this paper, we propose the approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describe the sequence of actions of the proposed approach. One of the first objectives of the sequence of actions is a speech detection issue. The paper gives a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian languages. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To illustrate the working capacity of the developed model, we have performed an analysis of speech detection and extraction from real tasks.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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Authors: Arunava Chakrabarti

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A one-dimensional chain of magnetic atoms, representative of a quantum gas in an artificial quasi-periodic potential and modeled by the well-known Aubry-Andre function and its variants are studied in respect of its capability of working as a spin filter for arbitrary spins. The basic formulation is explained in terms of a perfectly periodic chain first, where it is shown that a definite correlation between the spin S of the incoming particles and the magnetic moment h of the substrate atoms can open up a gap in the energy spectrum. This is crucial for a spin filtering action. The simple one-dimensional chain is shown to be equivalent to a 2S+1 strand ladder network. This equivalence is exploited to work out the condition for the opening of gaps. The formulation is then applied for a one-dimensional chain with quasi-periodic variation in the site potentials, the magnetic moments and their orientations following an Aubry-Andre modulation and its variants. In addition, we show that a certain correlation between the system parameters can generate absolutely continuous bands in such systems populated by Bloch like extended wave functions only, signaling the possibility of a metal-insulator transition. This is a case of correlated disorder (a deterministic one), and the results provide a non-trivial variation to the famous Anderson localization problem. We have worked within a tight binding formalism and have presented explicit results for the spin half, spin one, three halves and spin five half particles incident on the magnetic chain to explain our scheme and the central results.

Keywords: Aubry-Andre model, correlated disorder, localization, spin filter

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Authors: Alex Rodriguez, Adam Guerrero

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Purpose: This study is designed to examine the institutions that comprise the Online Consortium of Independent Colleges and Universities (OCICU) to understand better the types of higher education institutions that comprise their membership. The literature on this topic is extensive in analyzing the current economic environment around higher education, which is largely considered to be negative for independent, tuition-driven institutions, and is forcing colleges and universities to reexamine how the college-attending population defines value and how institutions can best utilize their existing resources (and those of other institutions) to meet that value expectation. The results from this analysis are intended to give OCICU the ability to target their current customer base better, based on their most notable differences, and other institutions to see how to best approach consolidation within higher education. Design/Methodology: This study utilized k-means cluster analysis in order to explore the possibility that different segments exist within the seventy-one colleges and universities that have comprised OCICU. It analyzed fifty different variables, whose selection was based on the previous literature, collected by the Integrated Postsecondary Education Data System (IPEDS), whose data is self-reported by individual institutions. Findings: OCICU member institutions are partitioned into two clusters: "access institutions" and "conventional institutions” based largely on the student profile they target. Value: The methodology of the study is relatively unique as there are not many studies within the field of higher education marketing that have employed cluster analysis, and this type of analysis has never been conducted on OCICU members, specifically, or that of any higher education consolidated offering. OCICU can use the findings of this study to obtain a better grasp as to the specific needs of the two market segments OCICU currently serves and develop measurable marketing programs around how those segments are defined that communicate the value sought by current and potential OCICU members or those of similar institutions. Other consolidation efforts within higher education can also employ the same methodology to determine their own market segments.

Keywords: Consolidation, Colleges, Enrollment, Higher Education, Marketing, Strategy, Universities

Procedia PDF Downloads 133